Interested in this AI/ML Engineer role at simPRO?
Apply Now →About This Role
Job Context
AI Sales Specialist — The Most Important Seat We’re Filling This Year
Read this twice, because we don’t write job postings like this often.
Many businesses in our customers’ world run on tight profit margins — on average around 5%.
We’ve built the AI back\-office solution to change that, helping customers work toward margins several times higher than they’re used to. Sit with that for a second. We are not asking you to squeeze more money out of customers — we’re asking you to help our customers become significantly more profitable than they’ve ever been. That’s the job. That’s the mission.
This is not order\-taking. This is providing real business solutions for our trades and field\-service management customers that are grinding on thin margins, showing them what AI can do to their
bottom line. You’ll be the person who introduces a transformation most of these businesses don’t even know is possible — and the better you are at it, the more companies you help change.What You’ll Do
What you’ll own
You’ll drive adoption of Simpro Group’s AI back\-office solutions across our existing customer base by pairing real technical command of the product with relentless, direct engagement. You’ll show customers — in their numbers, in their language — how AI can meaningfully lift their
margins. You’ll generate your own pipeline into non\-managed accounts; arm and support Account Managers on expansion deals; and become the person customers trust to reinvent how
their back office runs.
Day to day, you will:
- Introduce AI as the back\-office engine that can transform customer profitability — bringing
the technical firepower, demos, and direct engagement that turns interest into adoption.
- Be the product authority in the room, connecting our AI capabilities to exactly where a
customer is losing margin today.
- Work shoulder\-to\-shoulder with leadership and cross\-functional teams, driving outbound
into non\-managed accounts and backing Account Managers when deals are live.
- Run consistent, focused outbound into non\-managed accounts to build a pipeline of
customers ready to transform their economics.
- Carry — and crush — a defined adoption and expansion quota tied directly to the value
you put on customers’ bottom lines.
- Demonstrate and present our AI solutions with authority, translating the technology into
the one number customers care about most: profit.
- Step in for Account Managers on demos and technical conversations the moment an
opportunity opens.
- Know how our products integrate with each other and with the customer’s existing
technology stack to deliver that margin lift.
- Handle every technical question and objection customers throw at you as they evaluate
moving their back office to AI.
- Build and maintain deep mastery across the full portfolio — including new products and
acquisitions the day they land.
- Bring the voice of the customer back to product, shaping the roadmap with insight only a
frontline expert has.
- Stay sharp on industry trends and the competition so you can out\-position anyone in the
market.
Who we want
Someone bold. Someone who gets fired up by the idea of taking a business from surviving to
thriving. Someone with the technical chops to earn a customer’s respect and the conviction to
show them a future they can’t unsee.
If you’re the best, prove it here. The earning potential is uncapped, the mission is
enormous, and the runway is wide open.
What You’ll Bring
What We Can Offer You
- Responsible Time Off
- Comprehensive medical, dental, vision package with 100% employer paid options
- Additional benefits including Health Savings Account; Flexible Spending Account; Critical Illness Insurance; Hospital Insurance; Accident Insurance; Life Insurance and AD\&D; and Disability Insurance available to purchase.
- Wellness Challenge App, Diabetes Prevention App, and Health Hub App
- 401k/Retirement Plan with 6% employer match
- Generous Parental Leave Program
- Paid Volunteer Leave Days
- Public Holiday Exchange Scheme
- Talent Referral Program – get rewarded for referring a friend to join our team!
- Diverse training \& internal networking opportunities across all of our product lines
- Opportunities for career progression and development
- Service recognition awards
- Click here to find out more about working at Simpro Group!
Our Core Values
We Are One Team
We Are Customer Centric
We Are Growth Minded
We Are Accountable
We Celebrate Success
Simpro, AroFlo, BigChange \& ClockShark are equal opportunity employers with a best\-of\-class onboarding program and supportive team environments. This means that we want everyone to feel welcome with us and to provide equal opportunities for everyone, regardless of age, disability, gender reassignment, marriage and civil partnership, pregnancy and maternity, race, religion or belief, sex or sexual orientation, or any other non\-performance factor.
If you'd like to join a fun and progressive organization, where there are opportunities to develop your career, please apply now with your CV/resume.
- Please note, no agencies will be accepted in the recruitment of this role.
Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 3,823 AI roles we're tracking, AI/ML Engineer positions make up 69% of the market. At simPRO, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills in Demand for This Role
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $181,170 based on 12,692 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $165,000.
Across all AI roles, the market median is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($275,000) and AI Safety ($274,200). By seniority level: Entry: $97,880; Mid: $165,000; Senior: $227,400; Director: $247,800; VP: $250,000.
simPRO AI Hiring
simPRO has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Miami, FL, US.
Location Context
Across all AI roles, 15% (590 positions) offer remote work, while 3,217 require on-site attendance. Top AI hiring metros: New York (2,643 roles, $211,000 median); San Francisco (2,168 roles, $253,000 median); Los Angeles (1,792 roles, $191,580 median).
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 3,823 open positions tracked in our dataset. By seniority: 112 entry-level, 1,798 mid-level, 1,516 senior, and 397 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (590 positions). The remaining 3,217 roles require on-site or hybrid attendance.
The market median for AI roles is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($275,000 median, 41 roles); AI Safety ($274,200 median, 55 roles); Research Engineer ($260,000 median, 434 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 3,823 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,629), Data Scientist (322), AI Software Engineer (279). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (112) are outnumbered by mid-level (1,798) and senior (1,516) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 397 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (590 positions), with 3,217 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $200,100. Top-quartile roles start at $253,500, and the 90th percentile reaches $307,500. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Engineering Manager roles lead at $275,000 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,979 postings), Aws (1,190 postings), Azure (899 postings), Rag (839 postings), Gcp (726 postings), Pytorch (595 postings), Prompt Engineering (595 postings), Claude (540 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
Get Weekly AI Career Intelligence
Salary data, skills demand, and market signals from 16,000+ AI job postings. Every Monday.